Description of the effect of the practical management in the characterization of « terroir effect »

Purpose of this research is to quantitatively assess the mineral component of vineyard soils, with particular attention to the mineralogical analysis of clays, which represent an element of high importance in the vineyard culture as well as in general agriculture. An X-ray diffraction (XRD) / thermogravimetric (TG) multi-technique analytical approach was developed, tested on soil samples taken from vineyards around the world. This codified analytical procedure was necessary to obtain precise qualitative and quantitative mineralogical data, globally comparable to distinguish the geopedological identity of the vineyards. Soil samples from vineyards of various locations were analysed, in very different geological conditions. The bulk-rock quantitative phase analysis (QPA) was obtained by the Rietveld method while the detailed composition of the clay-sized fraction was determined by modelling of the oriented X-ray diffraction patterns. The research provided a precise classification of the mineral component of soils, distinguishing the mineral phases of the clays and the so-called mixed-layer clay minerals. We found that the content in mixed layers can be directly correlated with the water retention and the cation exchange capacity ​​of the soil, while the presence of other clayey minerals and phyllosilicates in this research did not affect this CEC parameter, which codes the fertility level of the soils. The study demonstrates that terroir, in particular soils formed in complex or very different geological conditions, can only be effectively interpreted by properly analysing its mineral phases, in particular the mixed-layer clay component. These are characteristic abiotic ecological indicators, which may have specific eco-physiological influences on the plant.

This study assessed the suitability of grapevine growing in three DOs (Empordà, Pla de Bages and Penedès) of Catalonia (NE Spain) over the 21st century. For this purpose, an estimation of water needs and agroclimatic and phenological indicators was made. Climate change impacts were estimated at 1 km pixel resolution using temperature and precipitation projections from several general circulation models (GCM) and two climate change scenarios: RCP 4.5 (stabilization scenario) and RCP 8.5 (worst-case scenario). Potential crop evapotranspiration (following FAO procedure) and a daily water balance considering soil water holding capacity were used to estimate actual evapotranspiration of vines and, finally, water needs. Dynamics would be similar in the three DOs studied although the magnitude of impact differs. Water needs would be 2 and 3 times greater (ranging from 0 to more than 1500 m3/ha) than current water needs at both climate change scenarios. Moreover, blooming date would advance from 3 to 6 weeks, harvest date from 1 to 2.5 months, resulting in growing cycles from 10 to 80 days shorter. It should also be noted that frost risk would decrease from 6 to 76%, the number of days with temperatures above 30ºC during ripening would rise from 48 to 500% and tropical nights (minimum temperature >20ºC) at ripening would increase from 28 to 150%, depending on the scenario and the DOs. The impacts of climate change in the three DOs could result in significant limitations for grapevine cultivation and wine production if adaptive strategies are not applied. This result could serve as a basis for the design of specific and particular adaptation strategies to improve and maintain vineyards in the DOs studied and could be extrapolated to similar DOs and regions.

Land use, plays a relevant role in the climatic system. It endows means for agriculture practices thus contributing to the food supply. Since climate and land are closely intertwined through multiple interface processes, climate change may lead to significant impacts in land use. In this study, 1-km observational gridded datasets are used to assess changes in the Köppen–Geiger and Worldwide Bioclimatic (WBCS)

Making high quality but affordable Pinot noir (PN) wine is challenging in most terroirs and New Zealand’s (NZ) situation is no exception. To increase the probability of making highly typical PN wines producers choose to grow grapes in cool climates on lower fertility soils while adopting labour intensive practices. Stringent yield targets and higher input costs necessarily mean that PN wine cost is high, and profitability lower, in line-priced varietal wine ranges. To understand the reasons why higher yielding vines are perceived to produce wines of lower quality we have undertaken an extensive study of PN in NZ. Since 2018, we established a network of twelve trial sites in three NZ regions to find individual vines that produced acceptable commercial yields (above 2.5kg per vine) and wines of composition comparable to “Icon” labels. Approximately 20% of 660 grape lots (N = 135) were selected from within a narrow juice Total Soluble Solids (TSS) range and made into single vine wines under controlled conditions. Principal Component Analysis of the vine, berry, juice and wine parameters from three vintages found grape berry mass to be most effective clustering variable. As berry mass category decreased there was a systematic increase in the probability of higher berry red colour and total phenolics with a parallel increase in wine phenolics, changed aroma fraction and decreased juice amino acids. The influence of berry size on wine composition would appear stronger than the individual effects of vintage, region, vineyard or vine yield. Our observations support the hypothesis that it is possible to produce PN wines that fall within an “Icon” benchmark composition range at yields above 2.5kg per vine provided that the Leaf Area:Fruit Weight ratio is above 12cm2 per g, mean berry mass is below 1.2g and juice TSS is above 22°Brix.

A large varietal collection including over 1700 varieties was maintained in Conegliano, ITA, since the 1950s. Phenological data on a subset of 400 grape varieties including wine grapes, table grapes, and raisins were acquired at bud break, flowering, veraison, and ripening since 1964. Despite the efforts in maintaining and acquiring data over such an extensive collection, the data set has varying degrees of missing cases depending on the variety and the year. This is ubiquitous in phenology datasets with significant size and length. In this work, we evaluated four state-of-the-art methods to estimate missing values in this phenological series: k-Nearest Neighbour (kNN), Multivariate Imputation by Chained Equations (mice), MissForest, and Bidirectional Recurrent Imputation for Time Series (BRITS). For each phenological stage, we evaluated the performance of the methods in two ways. 1) On the full dataset, we randomly hold-out 10% of the true values for use as a test set and repeated the process 1000 times (Monte Carlo cross-validation). 2) On a reduced and almost complete subset of varieties, we varied the percentage of missing values from 10% to 70% by random deletion. In all cases, we evaluated the performance on the original values using normalized root mean squared error. For the full dataset we also obtained performance statistics by variety and by year. MissForest provided average errors of 17% (3 days) at budbreak, 14% (4 days) at flowering, 14.5% (7 days) at veraison, and 17% (3 days) at maturity. We completed the imputations of the Conegliano dataset, one of the world’s most extensive and varied phenological time series and a steppingstone for future climate change studies in grapes. The dataset is now ready for further analysis, and a rigorous evaluation of imputation errors is included.